scholarly journals A survey on rendering homogeneous participating media

2021 ◽  
Vol 8 (2) ◽  
pp. 177-198
Author(s):  
Wenshi Wu ◽  
Beibei Wang ◽  
Ling-Qi Yan
Keyword(s):  
Fruit Juice ◽  
Single Scattering ◽  
Volume Density ◽  
Research Area ◽  
Open Problems ◽  
Participating Media ◽  
Spatially Correlated ◽  
Muddy Water ◽  
Acceleration Techniques ◽  
Incoming Light

AbstractParticipating media are frequent in real-world scenes, whether they contain milk, fruit juice, oil, or muddy water in a river or the ocean. Incoming light interacts with these participating media in complex ways: refraction at boundaries and scattering and absorption inside volumes. The radiative transfer equation is the key to solving this problem. There are several categories of rendering methods which are all based on this equation, but using different solutions. In this paper, we introduce these groups, which include volume density estimation based approaches, virtual point/ray/beam lights, point based approaches, Monte Carlo based approaches, acceleration techniques, accurate single scattering methods, neural network based methods, and spatially-correlated participating media related methods. As well as discussing these methods, we consider the challenges and open problems in this research area.

scholarly journals Fast Hyper-Spectral Radiative Transfer Model Based on the Double Cluster Low-Streams Regression Method

2021 ◽  
Vol 13 (3) ◽  
pp. 434
Author(s):  
Ana del Águila ◽  
Dmitry S. Efremenko
Keyword(s):  
Radiative Transfer ◽  
Single Scattering ◽  
Atmospheric Composition ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Absorption Bands ◽  
Acceleration Techniques ◽  
Scattering Approximation ◽  
Fine Resolution ◽  
Single Scattering Approximation

Fast radiative transfer models (RTMs) are required to process a great amount of satellite-based atmospheric composition data. Specifically designed acceleration techniques can be incorporated in RTMs to simulate the reflected radiances with a fine spectral resolution, avoiding time-consuming computations on a fine resolution grid. In particular, in the cluster low-streams regression (CLSR) method, the computations on a fine resolution grid are performed by using the fast two-stream RTM, and then the spectra are corrected by using regression models between the two-stream and multi-stream RTMs. The performance enhancement due to such a scheme can be of about two orders of magnitude. In this paper, we consider a modification of the CLSR method (which is referred to as the double CLSR method), in which the single-scattering approximation is used for the computations on a fine resolution grid, while the two-stream spectra are computed by using the regression model between the two-stream RTM and the single-scattering approximation. Once the two-stream spectra are known, the CLSR method is applied the second time to restore the multi-stream spectra. Through a numerical analysis, it is shown that the double CLSR method yields an acceleration factor of about three orders of magnitude as compared to the reference multi-stream fine-resolution computations. The error of such an approach is below 0.05%. In addition, it is analysed how the CLSR method can be adopted for efficient computations for atmospheric scenarios containing aerosols. In particular, it is discussed how the precomputed data for clear sky conditions can be reused for computing the aerosol spectra in the framework of the CLSR method. The simulations are performed for the Hartley–Huggins, O2 A-, water vapour and CO2 weak absorption bands and five aerosol models from the optical properties of aerosols and clouds (OPAC) database.

Control of flexible manipulators: A survey

Robotica ◽  
2004 ◽  
Vol 22 (5) ◽  
pp. 533-545 ◽  
Author(s):  
M. Benosman ◽  
G. Le Vey
Keyword(s):  
Linear Models ◽  
Control Strategies ◽  
Research Area ◽  
Future Research ◽  
Complex Nature ◽  
Open Problems ◽  
Complex Models ◽  
The Many ◽  
The One ◽  
Flexible Arms

A survey of the field of control for flexible multi-link robots is presented. This research area has drawn great attention during the last two decades, and seems to be somewhat less “attractive” now, due to the many satisfactory results already obtained, but also because of the complex nature of the remaining open problems. Thus it seems that the time has come to try to deliver a sort of “state of the art” on this subject, although an exhaustive one is out of scope here, because of the great amount of publications. Instead, we survey the most salient progresses – in our opinion – approximately during the last decade, that are representative of the essential different ideas in the field. We proceed along with the exposition of material coming from about 119 included references. We do not pretend to deeply present each of the methods quoted hereafter; however, our goal is to briefly introduce most of the existing methods and to refer the interested reader to more detailed presentations for each scheme. To begin with, a now well-established classification of the flexible arms control goals is given. It is followed by a presentation of different control strategies, indicating in each case whether the approach deals with the one-link case, which can be successfully treated via linear models, or with the multi-link case which necessitates nonlinear, more complex, models. Some possible issues for future research are given in conclusion.

scholarly journals Visual Computing and Machine Learning Techniques for Digital Forensics

2015 ◽  
Vol 22 (1) ◽  
pp. 128 ◽  
Author(s):  
Tiago Jose de Carvalho ◽  
Helio Pedrini ◽  
Anderson De Rezende Rocha
Keyword(s):  
Machine Learning ◽  
Digital Image ◽  
Digital Forensics ◽  
Research Area ◽  
Digital Image Forensics ◽  
Machine Learning Techniques ◽  
Open Problems ◽  
Visual Computing ◽  
Science Community ◽  
New Research

It is impressive how fast science has improved day by day in so many different fields. In special, technology advances are shocking so many people bringing to their reality facts that previously were beyond their imagination. Inspired by methods earlier presented in scientific fiction shows, the computer science community has created a new research area named Digital Forensics, which aims at developing and deploying methods for fighting against digital crimes such as digital image forgery.This work presents some of the main concepts associated with Digital Forensics and, complementarily, presents some recent and powerful techniques relying on Computer Graphics, Image Processing, Computer Vision and Machine Learning concepts for detecting forgeries in photographs. Some topics addressed in this work include: sourceattribution, spoofing detection, pornography detection, multimedia phylogeny, and forgery detection. Finally, this work highlights the challenges and open problems in Digital Image Forensics to provide the readers with the myriad opportunities available for research.

Customized Hardware Crypto Engine for Wireless Sensor Networks

2017 ◽  
Vol 7 (1) ◽  
pp. 263
Author(s):  
Medhat Awadalla ◽  
Ahmed Al Maashri ◽  
Lavanya Pathuri ◽  
Afaq Ahmad
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Reconfigurable Computing ◽  
Research Area ◽  
Wireless Sensor ◽  
Open Problems ◽  
Algorithmic Approach ◽  
Power Efficient ◽  
Alternative Routing ◽  
Active Research

Nowadays, managing for optimal security to wireless sensor networks (WSNs) has emerged as an active research area. The challenging topics in this active research involve various issues such as energy consumption, routing algorithms, selection of sensors location according to a given premise, robustness, and efficiency. Despite the open problems in WSNs, already a high number of applications available shows the activeness of emerging research in this area. Through this paper, authors propose an alternative routing algorithmic approach that accelerate the existing algorithms in sense to develop a power-efficient crypto system to provide the desired level of security on a smaller footprint, while maintaining real-time performance and mapping them to customized hardware. To achieve this goal, the algorithms have been first analyzed and then profiled to recognize their computational structure that is to be mapped into hardware accelerators in platform of reconfigurable computing devices. An intensive set of experiments have been conducted and the obtained results show that the performance of the proposed architecture based on algorithms implementation outperforms the software implementation running on contemporary CPU in terms of the power consumption and throughput.

scholarly journals A Survey on Differential Geometry of Riemannian Maps Between

2015 ◽  
Vol 0 (0) ◽  
Author(s):  
Bayram Şahin
Keyword(s):  
Differential Geometry ◽  
Riemannian Manifolds ◽  
Riemannian Geometry ◽  
Research Area ◽  
Riemannian Submersions ◽  
Open Problems ◽  
Geometric Objects ◽  
Riemannian Map

AbstractThe main aim of this paper is to state recent results in Riemannian geometry obtained by the existence of a Riemannian map between Riemannian manifolds and to introduce certain geometric objects along such maps which allow one to use the techniques of submanifolds or Riemannian submersions for Riemannian maps. The paper also contains several open problems related to the research area.

scholarly journals Compressed Sensing Radar Imaging: Fundamentals, Challenges, and Advances

Sensors ◽  
2019 ◽  
Vol 19 (14) ◽  
pp. 3100 ◽  
Author(s):  
Jungang Yang ◽  
Tian Jin ◽  
Chao Xiao ◽  
Xiaotao Huang
Keyword(s):  
Compressed Sensing ◽  
Radar Imaging ◽  
Research Area ◽  
Minimum Variance ◽  
Unbiased Estimation ◽  
Mathematical Framework ◽  
Open Problems ◽  
Imaging Methods ◽  
Active Research ◽  
Significant Attention

In recent years, sparsity-driven regularization and compressed sensing (CS)-based radar imaging methods have attracted significant attention. This paper provides an introduction to the fundamental concepts of this area. In addition, we will describe both sparsity-driven regularization and CS-based radar imaging methods, along with other approaches in a unified mathematical framework. This will provide readers with a systematic overview of radar imaging theories and methods from a clear mathematical viewpoint. The methods presented in this paper include the minimum variance unbiased estimation, least squares (LS) estimation, Bayesian maximum a posteriori (MAP) estimation, matched filtering, regularization, and CS reconstruction. The characteristics of these methods and their connections are also analyzed. Sparsity-driven regularization and CS based radar imaging methods represent an active research area; there are still many unsolved or open problems, such as the sampling scheme, computational complexity, sparse representation, influence of clutter, and model error compensation. We will summarize the challenges as well as recent advances related to these issues.

A brief introduction to the philosophy of information

2017 ◽  
Vol 12 (1) ◽  
Author(s):  
Anthony F. Beavers
Keyword(s):  
Research Area ◽  
Philosophy Of Information ◽  
Open Problems

The term “information” and its various meanings across several domains have spawned a growing research area in the discipline of philosophy known as the philosophy of information (PI). The following briefly outlines a taxonomy of the field addressing: 1) what is the philosophy of information; 2) what is information; 3) open problems in the philosophy of information; 4) paradoxes of information; 5) philosophy as the philosophy of information; 6) information metaphysics; and 7) information ethics.Keywords: Philosophy of information. Information.Link: http://revista.ibict.br/fiinf/article/view/3005/2755

scholarly journals Wireless Sensor Networks Formation: Approaches and Techniques

2016 ◽  
Vol 2016 ◽  
pp. 1-18 ◽  
Author(s):  
Miriam Carlos-Mancilla ◽  
Ernesto López-Mellado ◽  
Mario Siller
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Research Area ◽  
Wireless Sensor ◽  
Open Problems ◽  
Key Factor ◽  
Network Backbone ◽  
Active Research ◽  
Selection Of ◽  
Open Issues

Nowadays, wireless sensor networks (WSNs) emerge as an active research area in which challenging topics involve energy consumption, routing algorithms, selection of sensors location according to a given premise, robustness, efficiency, and so forth. Despite the open problems in WSNs, there are already a high number of applications available. In all cases for the design of any application, one of the main objectives is to keep the WSN alive and functional as long as possible. A key factor in this is the way the network is formed. This survey presents most recent formation techniques and mechanisms for the WSNs. In this paper, the reviewed works are classified into distributed and centralized techniques. The analysis is focused on whether a single or multiple sinks are employed, nodes are static or mobile, the formation is event detection based or not, and network backbone is formed or not. We focus on recent works and present a discussion of their advantages and drawbacks. Finally, the paper overviews a series of open issues which drive further research in the area.

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